A method may include obtaining an image representing a region of interest (ROI) of an object. The ROI may include two or more sub-regions. The method may include determining an average value of quantitative indexes associated with elements in the image corresponding to a first region of the ROI. The method may include determining, for each of the two or more sub-regions of the ROI, a threshold based on the average value; identifying target elements in the image based on the thresholds of the two or more sub-regions. The method may include assigning a presentation value to each of at least some of the target elements based on the average value and the quantitative index of the each target element. The method may include generating a presentation of the image based on the presentation values.
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2. The system of claim 1, wherein the ROI includes a volume of interest (VOI).
A system for medical imaging analysis defines a region of interest (ROI) within a scanned volume, such as a 3D medical image, to focus computational resources on a specific area. The ROI is further refined to include a volume of interest (VOI), which is a subset of the ROI that contains critical anatomical or pathological features. The system extracts and processes data from the VOI to enhance diagnostic accuracy, reduce processing time, and minimize irrelevant data analysis. The VOI may be automatically determined based on predefined criteria, such as tissue density, contrast differences, or user-defined parameters. The system may also allow manual adjustment of the VOI boundaries to ensure precise targeting of the relevant anatomical structures. By isolating the VOI within the broader ROI, the system improves efficiency in tasks such as tumor segmentation, lesion detection, or organ boundary delineation. The technology is particularly useful in radiology, where large datasets require optimized processing to support timely and accurate clinical decisions.
3. The system of claim 1, wherein the image includes a plurality of two-dimensional (2D) image slices.
The invention relates to a system for processing medical imaging data, specifically for analyzing three-dimensional (3D) images reconstructed from multiple two-dimensional (2D) image slices. The system addresses the challenge of accurately reconstructing and analyzing 3D medical images from 2D slices, which is critical for diagnostic and treatment planning in fields such as radiology and oncology. The system includes a data acquisition module that collects 2D image slices from imaging devices like CT or MRI scanners. These slices are then processed by a reconstruction engine that aligns and combines them into a coherent 3D volume. The system further includes an analysis module that applies algorithms to detect and quantify anatomical structures, lesions, or other features within the 3D image. The system may also incorporate machine learning techniques to enhance reconstruction accuracy or automate feature detection. The inclusion of 2D image slices allows for high-resolution imaging while maintaining computational efficiency. The system may be used in clinical settings to improve diagnostic accuracy, treatment planning, and monitoring of medical conditions.
5. The system of claim 4, wherein the presentation includes an illustration of at least one of the second region, the target area, the third region, the ROI, the first ratio, the second ratio, the third ratio, and the AHA segmental model.
This invention relates to medical imaging systems for analyzing cardiac anatomy and function, particularly for visualizing and quantifying regions of interest (ROIs) in the heart. The system addresses challenges in accurately assessing cardiac structures and their relationships during imaging procedures, such as identifying specific anatomical regions, target areas, and segmental models for diagnostic or therapeutic purposes. The system generates a presentation that includes visual representations of key cardiac regions, including a second region (e.g., a specific anatomical area), a target area (e.g., a site for intervention), a third region (e.g., an adjacent or overlapping area), and the ROI (a user-defined or algorithmically determined area of interest). The presentation also illustrates ratios derived from measurements of these regions, such as the first ratio (e.g., a ratio of the second region to the target area), the second ratio (e.g., a ratio of the target area to the third region), and the third ratio (e.g., a ratio of the ROI to the second region). Additionally, the system incorporates an American Heart Association (AHA) segmental model, which divides the heart into standardized segments for consistent analysis. The system dynamically updates the presentation based on real-time imaging data, allowing clinicians to assess spatial relationships and proportional measurements between cardiac regions. This enhances diagnostic accuracy and procedural planning by providing a comprehensive, visually integrated view of cardiac anatomy and functional metrics.
6. The system of claim 3, wherein the presentation includes at least one of the plurality of 2D image slices that includes an illustration of presentation values of the target elements within the at least one 2D image slice.
This invention relates to a system for visualizing and analyzing data from 2D image slices, particularly in medical imaging or scientific analysis. The system addresses the challenge of effectively presenting complex data from multiple 2D image slices in a way that highlights key target elements and their associated values. The system generates a presentation that includes at least one 2D image slice, where the slice is annotated with an illustration of presentation values corresponding to target elements within that slice. The target elements may represent specific features, structures, or regions of interest identified in the imaging data. The presentation values could include measurements, classifications, or other derived metrics associated with these elements. The system may also incorporate additional processing steps, such as segmenting the 2D image slices to isolate the target elements or applying algorithms to compute the presentation values. The visualization may use color coding, overlays, or other graphical techniques to clearly display the values alongside the original image data. This approach enhances the interpretability of the data, allowing users to quickly assess the significance of the target elements within the context of the 2D image slices. The system is particularly useful in applications where precise visualization of data values is critical, such as medical diagnostics, material science, or quality control.
7. The system of claim 1, wherein the presentation value of one of at least some of the target elements is a color value.
The invention relates to a system for visually presenting data elements, particularly focusing on enhancing the display of target elements within a dataset. The system addresses the challenge of effectively conveying information through visual attributes, ensuring clarity and interpretability for users. The core functionality involves assigning presentation values to target elements, where these values determine how the elements are displayed. In this specific aspect, the presentation value for at least some of the target elements is a color value, allowing users to distinguish or categorize the elements based on color. The system may include a data processing module to analyze the dataset and identify target elements, as well as a rendering module to apply the color values during visualization. This approach improves user interaction by leveraging color as a visual cue, making it easier to interpret complex data. The system can be applied in various fields, such as data analytics, user interfaces, or monitoring systems, where visual differentiation of elements is crucial. The use of color values enhances the system's ability to convey information efficiently, reducing cognitive load and improving decision-making.
8. The system of claim 1, wherein the first region of the ROI includes normal tissue within the ROI.
This invention relates to medical imaging systems for analyzing regions of interest (ROIs) in tissue samples, particularly for distinguishing between normal and abnormal tissue regions. The system includes an imaging device that captures images of a tissue sample, where the sample contains at least one ROI. The system processes these images to identify and segment different regions within the ROI, including a first region containing normal tissue and a second region containing abnormal tissue. The system then analyzes the segmented regions to generate diagnostic information, such as the presence, type, or severity of abnormalities. The imaging device may use techniques like optical coherence tomography, microscopy, or other imaging modalities to capture high-resolution images of the tissue. The system employs image processing algorithms to segment the ROI into distinct regions based on tissue characteristics, such as texture, color, or structural patterns. The segmentation process ensures that the first region, containing normal tissue, is accurately identified and separated from the second region, which may contain abnormal or diseased tissue. The system may also include a display for visualizing the segmented regions and a user interface for adjusting segmentation parameters. The diagnostic information generated by the system can assist healthcare professionals in making more accurate and timely diagnoses.
9. The system of claim 1, wherein the threshold for each of the two or more sub-regions of the ROI relates to a physiological condition of the ROI.
This invention relates to a medical imaging system designed to analyze regions of interest (ROIs) in physiological data, such as tissue or organ scans, to detect abnormalities. The system divides the ROI into two or more sub-regions and applies distinct thresholds to each sub-region to assess physiological conditions. Each threshold is tailored to the specific physiological characteristics of its corresponding sub-region, allowing for precise detection of deviations from normal conditions. The thresholds may be based on factors like tissue density, blood flow, metabolic activity, or other physiological parameters relevant to the sub-region. By dynamically adjusting thresholds for different sub-regions, the system improves accuracy in identifying abnormalities that may vary across the ROI. This approach is particularly useful in medical imaging applications where different parts of an organ or tissue exhibit different physiological behaviors, such as in tumor detection, vascular assessment, or functional imaging. The system enhances diagnostic reliability by accounting for spatial variations in physiological conditions within the ROI.
12. The system of claim 1, wherein the presentation includes a three-dimensional (3D) model corresponding to at least a portion of the ROI.
A system for medical imaging and analysis generates a three-dimensional (3D) model of a region of interest (ROI) within a patient's anatomy. The system captures medical imaging data, such as from computed tomography (CT) or magnetic resonance imaging (MRI), and processes the data to identify and isolate the ROI. The system then constructs a 3D model of the ROI, which can be displayed for visualization, analysis, or surgical planning. The 3D model may include anatomical structures, lesions, or other features of interest, allowing healthcare professionals to examine the ROI from multiple angles and perspectives. The system may also integrate additional data, such as patient records or previous imaging studies, to enhance the accuracy and context of the 3D model. This approach improves diagnostic precision, treatment planning, and patient outcomes by providing a detailed, interactive representation of the ROI. The system may be used in various medical fields, including radiology, oncology, and orthopedics, to support clinical decision-making and interventions.
13. The system of claim 12, wherein the 3D model includes an illustration of presentation values of at least a portion of the at least some target elements.
This invention relates to a system for visualizing and analyzing data in a three-dimensional (3D) model. The system addresses the challenge of effectively presenting complex data sets in a way that enhances user understanding and decision-making. The 3D model includes a representation of target elements, which are key data points or features of interest within the data set. The system further includes a visualization module that generates an illustration of presentation values for at least a portion of these target elements. These presentation values may include attributes such as color, size, or other visual indicators that convey additional information about the target elements, such as their importance, status, or relationships within the data. The system may also include a user interface that allows users to interact with the 3D model, enabling them to manipulate the view, filter data, or adjust presentation values to better analyze the information. The visualization module dynamically updates the 3D model in response to user inputs or changes in the underlying data, ensuring that the representation remains accurate and relevant. This system is particularly useful in fields such as scientific research, engineering, and business analytics, where complex data visualization can provide deeper insights and improve decision-making processes.
14. The system of claim 1, wherein the image includes one or more computed tomography (CT) images or magnetic resonance (MR) images.
This invention relates to a medical imaging system designed to enhance the analysis of anatomical structures using advanced imaging techniques. The system is configured to process and display medical images, particularly computed tomography (CT) images or magnetic resonance (MR) images, to improve diagnostic accuracy and clinical decision-making. The system includes a processing unit that receives and analyzes these images to extract relevant anatomical and pathological information. The processing unit may apply various image enhancement algorithms to improve image quality, such as noise reduction, contrast adjustment, or artifact correction. Additionally, the system may incorporate segmentation techniques to isolate specific anatomical regions of interest, aiding in the identification of abnormalities or lesions. The system also includes a display unit that presents the processed images in a user-friendly format, allowing healthcare professionals to visualize and interpret the data efficiently. The integration of CT and MR imaging modalities ensures comprehensive coverage of anatomical details, catering to different diagnostic needs. This system is particularly useful in scenarios where high-resolution imaging is required, such as in oncology, neurology, or cardiovascular diagnostics, to provide detailed insights into patient conditions.
15. The system of claim 1, wherein the ROI includes at least a part of a heart of the object.
This invention relates to medical imaging systems designed to analyze regions of interest (ROI) within biological objects, specifically focusing on cardiac imaging. The system captures and processes images to identify and analyze a region of interest that includes at least a portion of the heart. The primary challenge addressed is the accurate and efficient detection of cardiac structures in medical imaging data, which is critical for diagnosing and monitoring heart conditions. The system includes an imaging device that generates images of the object, such as a patient, and a processing unit that analyzes these images to isolate and examine the heart or a specific part of it. The processing unit applies image processing techniques to enhance the visibility of cardiac features, such as chambers, valves, or vessels, within the ROI. The system may also incorporate machine learning algorithms to improve the accuracy of heart detection and segmentation, ensuring reliable diagnostic results. Additionally, the system may include a display unit to visualize the analyzed ROI, allowing medical professionals to assess cardiac health. The imaging device can be any modality capable of capturing internal anatomical structures, such as MRI, CT, or ultrasound. The system ensures that the ROI is dynamically adjusted based on the imaging data, providing real-time or near-real-time analysis of the heart's condition. This approach enhances diagnostic precision and supports timely medical interventions.
16. The system of claim 1, wherein the quantitative index associated with the element includes signal intensity of the imaging signal associated with the element.
This invention relates to a system for analyzing imaging signals, particularly in medical or scientific imaging applications where precise quantification of signal data is critical. The system measures and processes imaging signals to generate a quantitative index for elements within an image, such as pixels or voxels. The quantitative index includes signal intensity, which represents the strength or amplitude of the imaging signal associated with each element. This allows for accurate assessment of features within the image, such as tissue density, contrast levels, or other measurable characteristics. The system may be used in modalities like MRI, CT, or ultrasound, where signal intensity variations provide diagnostic or analytical insights. By incorporating signal intensity into the quantitative index, the system enables enhanced precision in image analysis, improving diagnostic accuracy or research outcomes. The invention addresses challenges in imaging where subjective interpretation of signal strength can lead to inconsistencies, providing an objective, measurable metric for further processing or decision-making. The system may also include additional features, such as normalization or calibration of signal intensity values, to ensure consistency across different imaging sessions or devices.
18. The method of claim 17, wherein the quantitative index associated with the element includes signal intensity of the imaging signal associated with the element.
This invention relates to medical imaging systems, specifically methods for analyzing imaging signals to derive quantitative indices for elements within an image. The problem addressed is the need for more accurate and reliable quantification of imaging data, particularly in medical diagnostics where precise measurement of signal intensity can improve diagnostic accuracy. The method involves processing an imaging signal to identify elements within the image, such as anatomical structures or regions of interest. For each element, a quantitative index is generated, which includes the signal intensity of the imaging signal associated with that element. Signal intensity is a measure of the strength or amplitude of the detected signal, which can vary based on factors such as tissue density, contrast agent concentration, or other physiological properties. By incorporating signal intensity into the quantitative index, the method provides a more detailed and objective assessment of the imaged elements. The method may also involve additional steps such as normalizing the signal intensity to account for variations in imaging conditions or comparing the signal intensity of different elements to identify abnormalities. The quantitative index can be used for diagnostic purposes, treatment planning, or monitoring disease progression. The invention improves upon prior art by enhancing the precision and reliability of imaging-based measurements, which is particularly valuable in fields such as radiology, oncology, and cardiology.
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December 31, 2019
December 6, 2022
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